emotion recognition algorithm

Most existing models studying emotions are focused on separate characteristics of the emotional process: emotional arousal and conduct, as opposed to identifying particular emotional states.

Natalia Galkina will present the results of her team’s research that relate to the machine learning of an emotion recognition algorithm. The research was inspired by the idea of drawing up an emotional profile of viewers after watching affective stimuli. Such a profile could help predict an emotional advertising pattern. Natalia and her team discovered how to obtain an emotional pattern of a stimulus; emotional recognition.

Follow her through the steps that led to gaining a more complex and differentiated understanding about discerning how potential customers experience emotional stimulants.

Audience takeaways:

- Discover the relationships between self-assessing emotional states and EEG activity - Get a broader perception on how certain emotions come in to play in predictive models- Boost your understanding about what emotional processes elicit in the human brain